As we approach 2026, artificial intelligence is no longer just a technological luxury or a topic for conferences; it has become an increasingly present part of nonprofit organizations, especially in areas like fundraising, grant writing, donor data analysis, and enhancing small team efficiency.
This text is based on an article published on the Julep CRM blog titled: AI, Fundraising, and the Future of Nonprofits: What 2026 Holds, which we at "The Third Bank" translated and adapted while preserving the author's and original source's literary rights.
As we near 2026, artificial intelligence is no longer a futuristic idea for nonprofits; it is a present reality, growing rapidly, and reshaping what is possible within this sector. For many years, nonprofits have faced a harsh equation: limited funding, overworked teams, and increasing demand for services. Today, a new question has emerged on the tables of boards of directors, resource development offices, and program teams:
"Can artificial intelligence help us accomplish more with fewer resources... and with better quality?"
The answer is increasingly leaning towards: yes. But this 'yes' is contingent upon conscious planning, clear standards, and a mindset that puts people first.
Adopting Artificial Intelligence in the Nonprofit Sector: A Turning Point
According to the AI Equity 2025 project, 65% of nonprofits say they are interested in artificial intelligence. Furthermore, nearly 90% of organizations with a stated social mission use some form of AI, and around three-quarters report noticing real improvements in productivity and efficiency.
Nevertheless, the adoption journey is still in its early stages for most organizations. The focus is often on internal uses like automating grant writing, donor research, and impact reports, which is clearly visible with small teams. Research by the Fast Forward Foundation has shown that smaller organizations are bolder in their adoption, leveraging ready-made tools and AI models trained on publicly available data to streamline their operations.
However, the level of interest far exceeds the level of readiness. Only 9% of nonprofits feel confident in their ability to adopt artificial intelligence responsibly. A third do not yet see how AI can intersect with their core mission. And less than half of these organizations have a clear policy for using artificial intelligence or for its ethical framework.
With the increasing accessibility of AI technologies, organizations have started experimenting and integrating new tools into their work. Most start with small steps, monitor the results, and then expand what proves successful.
From Idea to Capability: How Does Artificial Intelligence Create Real Impact?
Nonprofits today are not just "experimenting" with artificial intelligence; many are beginning to see how this transformation is fundamentally changing the way they operate. Interestingly, this future does not belong solely to large entities; it is making its way through small, focused organizations that have decided to start with simple steps, experiment, and then expand what works.
Take the example of Pets for Patriots, where executive director Beth Zimmerman used an AI tool to reduce the time spent writing grant applications by about 90%. What used to take her two full days can now be done in just a few hours. The result? More applications submitted, more funding, and additional time that can be invested in strategy and relationship-building.
In Prospect Sierra School, an AI tool helped the team generate real-time reports on potential donors, which previously took hours of manual research. Instead of navigating through databases and piecing together notes, resource development teams can now focus their efforts on personal communication with donors.
Anthos Home, a housing-focused organization in New York, uses AI to match applicants with available apartments based on a complex mix of needs, voucher types, and geographical constraints. AI does not make the final decision, but it presents the best options on the table, enabling human team members to focus on helping people instead of drowning in spreadsheets and manual sorting.
These examples are not fanciful projects or space-age experiments; they are practical, accessible models that are becoming increasingly affordable to adopt day by day. More importantly, they achieve tangible improvements in impact, outreach, and the sustainability of organizations' work.
What Obstacles Face Nonprofits?
Despite the increasing pace of adoption, there are still fundamental barriers hindering the path:
Funding Gaps: According to the AI for Humanity 2025 report, 84% of nonprofits reported needing additional investments to expand AI use. Many noted an increase in expenses after starting to use these technologies, while a few funders currently support AI initiatives directly.
Skills Shortage: Most nonprofits do not have budgets for specialized training in AI, nor do they have dedicated technical teams for this purpose. Hiring a data scientist is often beyond their financial capacity. However, there are alternative solutions, such as pro bono partnerships, student training, and time donation programs from specialists in technology and data.
Cultural Resistance: Some employees may be wary of automation or feel overwhelmed by rapid changes. Here, the role of conscious change management, comprehensive implementation plans involving the team, explaining the benefits, and allowing space for questions and natural concerns come into play.
Funders also have work to do. While 81% of funding institutions report testing AI internally, only 5% fund AI tools for the grantees of their grants. Closing this gap will be critical if the sector wants to unlock the full potential of artificial intelligence.
Action Guide for 2026 and Beyond
What should nonprofit leaders do now?
Start Small... and Demonstrate Value: Choose just one course of action. Try a low-risk AI tool, such as a grant writing assistant or a donor research platform. Monitor what changes in terms of time, quality, and outcomes, and then gradually build upon that.
Establish a Clear Policy for Responsible AI Use: Even if it's simple at first. Define the boundaries, what is acceptable and what is unacceptable, the tools allowed, and inform your team of these guidelines.
Invest in Data 'Cleanliness': AI predictive models are no better than the quality of the data they are fed. Donor and program data must be clean, unified, and analytically usable.
Engage the Community and Beneficiaries: Seek feedback from the people your organization serves. Ensure that AI tools reflect their needs, languages, and lived experiences rather than imposing an alien logic onto them.
Build the AI Team in Innovative Ways: Consider volunteers, pro bono technical support, or partnerships with universities and student technology and data programs as an initial entryway without significant financial burdens.
Be Honest with Funders About Your Needs: Present AI not as "additional administrative costs" but as a multiplier for programs and impact. Connect your request to clear examples of how it contributes to maximizing effectiveness, enhancing efficiency, and improving sustainability over the long term.
A Powerful Tool for Enhancing Efficiency
Artificial intelligence is not a magical solution for everything... but it is also not just passing noise.
For nonprofits, it represents one of the strongest tools in decades for driving mission-related innovation, alleviating administrative burdens, and maximizing real-world impact, especially in times of resource scarcity.
The organizations that will thrive in 2026 and beyond will not necessarily be the largest; they will be those most capable of adapting. These entities do not just ask:
"Can artificial intelligence help us write a better grant?" They pose a deeper question: "How can we reimagine our entire business model if knowledge were abundantly available and implementation was nearly instantaneous?"
This future is not five years away; it is being made today, chatbots by chatbots, one grant request at a time, and intelligent matching between beneficiaries and programs each time.
The most critical question: Will your organization be among those prepared for this transformation... or will it watch from the sidelines?
In light of this transformation, artificial intelligence seems less like an "optional extra" and more like a new infrastructure for nonprofit work. The question is no longer: Will we use these tools or not? But rather: How do we use them in a way that protects our mission, respects the beneficiary, and enhances donor trust instead of putting it at risk? Organizations that start early in organizing their data, establishing clear policies for AI use, and building insightful and technical partnerships will be the most capable of transforming this wave into an opportunity for maximizing impact rather than a source of new confusion.
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